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The Award database is continually updated throughout the year. As a result, data for FY24 is not expected to be complete until March, 2025.

Download all SBIR.gov award data either with award abstracts (290MB) or without award abstracts (65MB). A data dictionary and additional information is located on the Data Resource Page. Files are refreshed monthly.

The SBIR.gov award data files now contain the required fields to calculate award timeliness for individual awards or for an agency or branch. Additional information on calculating award timeliness is available on the Data Resource Page.

  1. Machine Learning Integrated CMOS Terahertz Focal Plane Arrays

    SBC: PRIXARC LLC            Topic: OSD222D02

    Prixarc proposes to develop and commercialize novel terahertz (THz) focal-plane array (FPA) that utilizes 3D microstructures, smart readout integrated circuits, and allows efficient integration with processors that incorporate machine learning to increase the data collection efficiency. We plan to collaborate with University of Miami (UM) and Kansas State University (KSU) for this project. We prop ...

    SBIR Phase II 2023 Department of DefenseNational Geospatial-Intelligence Agency
  2. Geography Aided Inference ATR (GAIA)

    SBC: ETEGENT TECHNOLOGIES, LTD.            Topic: OSD221001

    The amount of data collected from the suite of current and future sensors far surpasses the bandwidth of analysts to processes the data streams into actionable intelligence. This pixel to pupil ratio problem is a forcing function for developing robust algorithms which accurately find non-cooperative objects while minimizing the false alarm rate.  As exploitation algorithms are tasked with perform ...

    SBIR Phase I 2022 Department of DefenseNational Geospatial-Intelligence Agency
  3. Automated Learning from Unsupervised Repositories of Data (ALURD)

    SBC: ETEGENT TECHNOLOGIES, LTD.            Topic: NGA201003

    The need for automated labelling of overhead data is obvious, less obvious is that these unlabelled images provide an opportunity to improve autonomous labelers making them more accurate and more dynamic. Extracting even a small amount of information from the stream of unlabelled samples has the potential to massively impact the quality of machine learners for remotely sensed imagery. The proposer ...

    SBIR Phase II 2022 Department of DefenseNational Geospatial-Intelligence Agency
  4. Novel Mathematical Foundation for Automated Annotation of Massive Image Data Sets

    SBC: SKYWARD, LTD.            Topic: NGA203005

    Modern Artificial Intelligence (AI) solutions generally employ carefully-crafted Neural Networks (NNs) that require extensive human effort to perform detection, identification, and annotation on each image to create training datasets. AI tools are desired that are optimized for object identification and annotation across diverse families of image data, are reliable and robust, not dependent on e ...

    SBIR Phase I 2022 Department of DefenseNational Geospatial-Intelligence Agency
  5. SWaP-C Efficient High-Resolution High-Speed Digitizer and Processor

    SBC: PRIXARC LLC            Topic: NGA192001

    Prixarc proposes to develop and commercialize an efficient, fast, and low size, weight, power, and cost (SWaP-C) digitizer and processor system for use with fast photodetectors. High-speed data converters are critical in building a fast and a reliable photon detector in a small form factor. The specific goal is to design an analog to digital converter (ADC) with sampling rate of 10 Giga samples pe ...

    SBIR Phase II 2021 Department of DefenseNational Geospatial-Intelligence Agency
  6. Low-shot Automated Performance Prediction via Transfer Learning

    SBC: ETEGENT TECHNOLOGIES, LTD.            Topic: NGA20C001

    Low-shot objection recognition has become an area of active research in recent years, with advances dramatically improving performance when only a few samples are available, nominally fewer than 20. These technologies are a focus of the intelligence community (IC) because this challenge pertains to many intelligence problems, e.g., objects of interest are rare due to their use, sensitive nature, ...

    STTR Phase I 2021 Department of DefenseNational Geospatial-Intelligence Agency
  7. CLOAKT (Classification of Low-shot Objects via Attributed Knowledge Transfer)

    SBC: ETEGENT TECHNOLOGIES, LTD.            Topic: NGA172002

    The intelligence community is faced with an increasingly difficult challenge: the amount of data far outstrips the number of analysts that exploit this data into actionable information. With the ever-growing number of imaging satellites in orbit the job of an analyst will change from eyes on pixels to analysis of information from imagery thanks to automated image processing like object detection a ...

    SBIR Phase II 2021 Department of DefenseNational Geospatial-Intelligence Agency
  8. SWaP-C Efficient High-Resolution High-Speed Digitizer and Processor

    SBC: PRIXARC LLC            Topic: NGA192001

    We propose to develop an efficient, fast, and low size, weight, power, and cost (SWaP-C) digitizer for use with fast  photodetectors. High-speed data converters are critical in building a fast-reliable photon detector in a small form factor. We propose to combine i) ultra-low power analog design techniques, ii) well-known adaptive ADC topologies, iii) signal coherence Digital Signal Processing ( ...

    SBIR Phase I 2020 Department of DefenseNational Geospatial-Intelligence Agency
  9. ALURD: Automated Learning from Unsupervised Repositories of Data

    SBC: ETEGENT TECHNOLOGIES, LTD.            Topic: NGA201003

    Etegent proposes Automated Learning from Unsupervised Repositories of Data (ALURD). ALURD incorporates a trained detector to feed a semi-supervised discrimination apparatus that leverages state-of-the-art approaches.in semi-supervised learning (SSL).  The need for automated labelling of overhead data is obvious, less obvious is that these unlabelled images provide an opportunity to improve auton ...

    SBIR Phase I 2020 Department of DefenseNational Geospatial-Intelligence Agency
  10. SURFER: SAR Unsupervised and Robust Feature ExtractoR

    SBC: THE DESIGN KNOWLEDGE COMPANY LLC            Topic: NGA191001

    The NGA requires an automatic, unsupervised SAR feature extraction (AUFE) technique, that can ultimately be deployed for geospatial analysis, modeling, and target detection. Our proposed “SAR Unsupervised and Robust Feature ExtractoR” (SURFER) solution includes in Phase I: (1) a sound and deterministic assessment of the underlying RF phenomenology and SAR processing theoretical basis for effec ...

    SBIR Phase I 2019 Department of DefenseNational Geospatial-Intelligence Agency
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